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The Effects of Diagnostic Definitions in Claims Data on Healthcare Cost Estimates: Evidence from a Large-Scale Panel Data Analysis of Diabetes Care in Japan

Author

Listed:
  • Haruhisa Fukuda

    (Kyushu University Graduate School of Medical Sciences)

  • Shunya Ikeda

    (International University of Health and Welfare)

  • Takeru Shiroiwa

    (National Institute of Public Health)

  • Takashi Fukuda

    (National Institute of Public Health)

Abstract

Background Inaccurate estimates of diabetes-related healthcare costs can undermine the efficiency of resource allocation for diabetes care. The quantification of these costs using claims data may be affected by the method for defining diagnoses. Objectives The aims were to use panel data analysis to estimate diabetes-related healthcare costs and to comparatively evaluate the effects of diagnostic definitions on cost estimates. Research design Monthly panel data analysis of Japanese claims data. Subjects The study included a maximum of 141,673 patients with type 2 diabetes who received treatment between 2005 and 2013. Measures Additional healthcare costs associated with diabetes and diabetes-related complications were estimated for various diagnostic definition methods using fixed-effects panel data regression models. Results The average follow-up period per patient ranged from 49.4 to 52.3 months. The number of patients identified as having type 2 diabetes varied widely among the diagnostic definition methods, ranging from 14,743 patients to 141,673 patients. The fixed-effects models showed that the additional costs per patient per month associated with diabetes ranged from US$180 [95 % confidence interval (CI) 178–181] to US$223 (95 % CI 221–224). When the diagnostic definition excluded rule-out diagnoses, the diabetes-related complications associated with higher additional healthcare costs were ischemic heart disease with surgery (US$13,595; 95 % CI 13,568–13,622), neuropathy/extremity disease with surgery (US$4594; 95 % CI 3979–5208), and diabetic nephropathy with dialysis (US$3689; 95 % CI 3667–3711). Conclusions Diabetes-related healthcare costs are sensitive to diagnostic definition methods. Determining appropriate diagnostic definitions can further advance healthcare cost research for diabetes and its applications in healthcare policies.

Suggested Citation

  • Haruhisa Fukuda & Shunya Ikeda & Takeru Shiroiwa & Takashi Fukuda, 2016. "The Effects of Diagnostic Definitions in Claims Data on Healthcare Cost Estimates: Evidence from a Large-Scale Panel Data Analysis of Diabetes Care in Japan," PharmacoEconomics, Springer, vol. 34(10), pages 1005-1014, October.
    • Handle: RePEc:spr:pharme:v:34:y:2016:i:10:d:10.1007_s40273-016-0402-3
    DOI: 10.1007/s40273-016-0402-3
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    References listed on IDEAS

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    1. Ulf-G Gerdtham & Philip Clarke & Alison Hayes & Soffia Gudbjornsdottir, 2009. "Estimating the Cost of Diabetes Mellitus-Related Events from Inpatient Admissions in Sweden Using Administrative Hospitalization Data," PharmacoEconomics, Springer, vol. 27(1), pages 81-90, January.
    2. Till Seuring & Olga Archangelidi & Marc Suhrcke, 2015. "The Economic Costs of Type 2 Diabetes: A Global Systematic Review," PharmacoEconomics, Springer, vol. 33(8), pages 811-831, August.
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